Anti-forensic approach for JPEG compressed images with enhanced image quality and forensic undetectability

Most of the detectors employed in digital image forensics are based on JPEG compression. To determine the capability of these forensic detectors, proficient anti-forensic techniques that challenge and help in the upgradation of forensic techniques are required. This paper proposes an anti-forensic technique based on the shifted block Discrete Fractional Cosine Transform (DFrCT) approach. Afterwards, Total variation (TV) -based deblocking operation is used in order to remove the compression blocking artifacts. Due to the shifted block approach, the proposed method performs histogram smoothing without adding any dithering signal, which means that it is capable of applying dithering by itself. Further, to remove blocking artifacts which are left during the JPEG compression TV-based deblocking is used. The DFrCT approach provides an additional fractional parameter to improve the accuracy of the proposed approach. The proposed scheme is evaluated based on the UCID dataset images by considering the scalar based and machine learning-based forensic detectors. It is observed from the experimental results that the proposed approach provides improved performance in terms of PSNR, SSIM, and forensic undetectability when compared to existing techniques. The analysis performed in this paper challenges the security and robustness of JPEG compression forensic techniques.